Abstract
We present a versatile and model based procedure for estimating a density in a deconvolution setting where the error density is assumed to be singular enough.We assess the quality of our estimator by establishing non-asymptotic risk bounds for the $\mathbb{L}^1$ loss. We specify them when the density is piecewise constant on a finite number of (unknown) pieces, when it is unimodal, and when it is concave/convex.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
